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Comment by lbacaj | Hacker News Reader

This was just posted and already there are two types of comments:

1. Most devs don’t need this, it’s not so helpful to know etc.

2. These are critical numbers to know and in the very least devs should know these numbers.

This sort of disagreement is common in our industry, it’s not just this it’s also Big O, algorithms and data structures, and even OS fundamental people disagree on.

I’d love to take both groups of devs commenting and give each group a set of programming tasks to complete. Judge them based on correctness, speed of development, speed the tasks run, the quality of the code etc, etc.

I think the results would be profound.

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Is it but because our jobs are so varied? My team implements what I would call "business logic" for a (relative to Google scale) small number of users. We often frown at algorithmic coding exercises, like what we believe Google would ask in interviews, using the argument: we suppose that makes sense if you have to optimize compression of YouTube's video streams, which we don't have to... (Rather, our small, ambitious team emphasizes optimization for maintainability over performance.)

In my experience, at least, the vast majority of software development jobs are developing this kind of 'enterprise' infrastructure. The technical details are usually straightforward and the complexity is in meeting the needs of the users and the business, and the amount of processing required is trivial on modern computers to the point where implementation performance almost never matters.

Jobs where you need to do anything tricky or performance-sensitive, where it's worth knowing fancy algorithms and low level implementation details, are few and far between.

You'd then also have to give each dev a task representative of the kind of work they nah do on a daily basis.

I think you'd find probably people are good at what they spend time doing a lot and tend to brush off things they don't as not important.

Alternatively, find successful startups and find who coded their MVP or whatever they started with, and see which type of dev has more success.

I'm guessing the results won't be as lopsided and "profound."

Correctness, quality, speed are not always defining metrics (and sometimes they definitely are!).

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